This paper discusses the potential of a spatial microsimulation-based decision support system for policy analysis. The system can be used to describe current conditions and issues in neighbourhoods, predict future trends in the composition and health of neighbourhoods and conduct modelling and predictive analysis to measure the likely impact of policy interventions at the local level. A large dynamic spatial micro-simulation model is being constructed for the population of Leeds (approximately 715,000 individuals) based on spatial microsimulation techniques in conjunction with a range of data, including 2001 Census data for Output Areas and sample data from the British Household Panel Survey. The project has three main aims as follows: (i) to develop a static microsimulation model to describe current conditions in Leeds; (ii) to enable the performance of ‘What if?’ analysis on a range of policy scenarios; and (iii) to develop a dynamic microsimulation model to predict future conditions in Leeds under different policy scenarios. The paper reports progress in meeting the above aims and outlines the associated difficulties and data issues. One of the significant advantages of the spatial microsimulation approach adopted by this project is that it enables the user to query any combination of variables that is deemed desirable for policy analysis. The paper will illustrate the software tool being developed in the context of this project that is capable of carrying out queries of this type and of mapping their results. The decision support tool is being developed to support policy-makers concerned with urban regeneration and neighbourhood renewal.

Ballas, D, Kingston R, Stillwell, J, (2003) Public participation in local policy-making with the use of GIS-based microsimulation
, Poster presented at the 2nd annual Public Participation GIS Conference, Portland State University, Portland, USA, 20-22 July 2003

Williamson, P., Birkin, M. and Rees, P. (1998) The estimation of population microdata by using data from small area statistics and samples of anonymised records
, Environment and Planning A, 30: 785-816